class_docstr: Return conditioned Behavior cloning agent.
code: def _build_networks_and_optimizer(self):
      self._rng, rng = jax.random.split(self._rng)
      self.online_params = self.network_def.init(
          rng,
          x=self.state,
          support=self._support,
          return_to_condition=jnp.array(0.0, dtype=jnp.float32),
      )
      self.optimizer = dqn_agent.create_optimizer(self._optimizer_name)
      self.optimizer_state = self.optimizer.init(self.online_params)
      self.target_network_params = self.online_params
  
imports: import functools
  from absl import logging
  from dopamine.jax import losses
  from dopamine.jax.agents.dqn import dqn_agent
  from dopamine.jax.agents.rainbow import rainbow_agent
  from dopamine.labs.offline_rl.jax import offline_rainbow_agent
  import gin
  import jax
  import jax.numpy
  import numpy
  import optax
  import tensorflow
label_desc: Use image node_id 3 for calling the JaxReturnConditionedBCAgent obj's underlying member method code with example usage: obj._build_networks_and_optimizer() without return types